Virtual microscopy is a technology that gives physicians the ability to navigate and observe a biological specimen as though they were controlling a microscope. This can be achieved using a display device such as a computer monitor or tablet with access to a database of microscope images of the specimen. Enhanced observation of biological specimens can afford physicians greater opportunity to perform a medical diagnosis upon the subject from which the specimens were obtained.
Capture of images for virtual microscopy is generally performed using a high throughput slide scanner. The specimen is loaded mechanically onto a stage and moved under the microscope objective as images of different parts of the specimen are captured on a sensor. Any two adjacent captured images have a region of overlap so that the multiple images of the same specimen can be combined, or spliced, to form a two-dimensional (2D) layer or a three-dimensional (3D) volume.
Alternatively, Fourier Ptychographic Microscopy (FPM) can be used for whole slide imaging. FPM is able to produce a high resolution and wide field of view image without a need for transverse motion of the specimen under the objective lens. This is achieved by capturing many intensity images of the specimen under different lighting conditions, and combining the images in the Fourier domain using an iterative computational process.
Virtual microscopy can be applied to image histology specimens prepared from a tissue sample by freezing the sample in paraffin and then slicing into sections or layers. The slices may be stained to reveal particular features, and placed on a microscope slide under a cover slip. These specimen slides are then converted into digital slides by virtual microscopy. A clinician may subsequently examine several adjacent digital slides of the specimen tissue to assess the extent of a disease throughout the tissue. Accordingly, it is often desirable to align the digital slides so that a clinician can easily assess the tissue sample.
There may, however, be complex, nonlinear deformations between adjacent digital slides, which make registration of digital slides difficult. One such factor is the physical axial distance between the digital slides. For instance, if the axial distance between two adjacent sections is large, the digital slides of these sections may contain less common features upon which registration may be performed. Another factor may be variations in the sections introduced when the sections are cut. For instance, striations (ridges), folds, tears, or other physical deformations may be introduced independently to the sections during cutting. A third factor may be variations in the sections caused by staining the section. For instance, different preparations applied to the tissue for staining may be different between sections and cause the same feature to appear quite differently when imaged.
In spite of the difficulties, a variety of registration methods may be employed to align digital slides including, optical or normal flow based methods, information-theoretic methods (e.g. mutual information), cross-correlation-based methods, gradient based methods, and more recently methods that utilize advanced statistical methods from machine learning. Additionally, there are many ways to model the non-linear deformations that occur between images that either take into account a physical-based model of tissue deformations, such as elastic material deformation or fluid flow, or attempt to model the deformations using basis functions such as radial basis functions, wavelet transforms, and B-splines.
However, such methods are usually slow when applied to large (e.g. 25,000 by 25,000 pixels) whole slide images. For example, it may take tens of minutes to register two 25,000×25,000 pixel images depending on the techniques used, making virtual microscopy practically difficult to use by clinicians. Therefore, there is a need to improve overall throughput of the virtual microscopy systems, particularly, to provide registered images of adjacent slides to a clinician faster.